The future of data analytics in the legal industry

Data is often seen as the new oil or the new gold – a resource that is useless if left "unrefined"; only once it’s mined and analysed, does it create value. Given that we live in a data-driven age, it's not surprising that data is perceived as a precious commodity.

The application of data analysis methods and technologies in law is generally referred to as "legal analytics". Examples of legal analytics include:

• big data analytics – providing insights from large data sets
• predictive analytics – predicting future behaviour from past data
• artificial intelligence (AI) – self-learning technology akin to human intelligence

The legal industry is still in a very early stage of adoption of legal analytics; however, most law firms or corporate legal departments now acknowledge the importance of better data capture and recognise that their focus in this area should extend beyond mere financial data.

Finding value and opportunity in data

Law firms that do not collect and analyse data miss out on opportunities to improve their client experience, mitigate risk, and maximise their profits.

A proper appreciation for and collection of data, such as capturing outcome and settlement data for all litigation matters, helps position an organisation for artificial intelligence and advanced analytics. As data stores in the legal sector grow, so will the latent value within that collected data.

A threat to traditional legal roles?

Growing interest in applying AI to law is slowly transforming the profession and closing in on the work of paralegals, legal researchers, and litigators, which will continue as the technology matures. But with this perceived threat comes the opportunity to dramatically rethink how work is done.

In a 2016 report, Deloitte predicted that 100,000 legal roles will be automated by 2036. The report stated that by 2020 law firms will be faced with a “tipping point” for a new talent strategy. Now is the time for all law firms to commit to becoming AI-ready by embracing a growth mindset, setting aside their fear of failure and taking steps to develop internal AI practices.

Current applications of AI fall into six key categories:

• Due diligence – Litigators perform due diligence with the help of AI tools to uncover background information. Contract review, legal research and electronic discovery are included in this section
• Prediction technology – An AI software generates results that forecast litigation outcome
• Legal analytics – Lawyers can use data points from past case law, win/loss rates and a judge’s history to identify trends and patterns
• Document automation – Law firms use software templates to complete documents based on data input
• Intellectual property – AI tools guide lawyers in analysing large IP portfolios and drawing insights from the content
• Electronic billing – Lawyers’ billable hours are computed automatically

From a client perspective, AI will have the following impacts:

• Recasting the relationship dynamic: AI will lead to greater efficiency and challenge revenue models, which will drive enhanced engagement and a more collaborative relationship model
• Embracing new business models: Clients expect their legal provider to be innovative and adopt new technologies to challenge existing processes
• Reshaping the talent pool: Clients will expect an increased reliance on legal analytics technology. As a result, future lawyers will need to take advantage of technology and equip themselves with the skills needed to implement data analytics.

While some might still perceive legal analytics technology as a threat to the traditional legal sector, it also presents numerous opportunities to capitalise on emerging trends and allow lawyers to focus on the intellectually engaging aspects of law, instead of the mundane and tedious. There's no doubt this will ultimately improve the profession of law, for both lawyers and our clients.